[GitHub] [hudi] yihua commented on a diff in pull request #8342: [HUDI-5987] Fix clustering on bootstrap table with row writer disabled

["yihua (via GitHub)" <gi...@apache.org>]

yihua commented on code in PR #8342:
URL: https://github.com/apache/hudi/pull/8342#discussion_r1169374327


##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/clustering/run/strategy/MultipleSparkJobExecutionStrategy.java:
##########
@@ -368,6 +404,8 @@ private Dataset<Row> readRecordsForGroupAsRow(JavaSparkContext jsc,
         .stream()
         .map(op -> {
           ArrayList<String> readPaths = new ArrayList<>();
+          // NOTE: for bootstrap tables, only need to handle data file path (ehich is the skeleton file) because

Review Comment:
   ```suggestion
             // NOTE: for bootstrap tables, only need to handle data file path (which is the skeleton file) because
   ```



##########
hudi-common/src/main/java/org/apache/hudi/io/storage/HoodieBootstrapFileReader.java:
##########
@@ -0,0 +1,117 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi.io.storage;
+
+import org.apache.hudi.avro.HoodieAvroUtils;
+import org.apache.hudi.common.bloom.BloomFilter;
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.model.MetadataValues;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.collection.ClosableIterator;
+
+import org.apache.avro.Schema;
+
+import java.io.IOException;
+import java.util.Set;
+
+public abstract class HoodieBootstrapFileReader<T> implements HoodieFileReader<T> {
+
+  private final HoodieFileReader<T> skeletonFileReader;
+  private final HoodieFileReader<T> dataFileReader;
+
+  private final Option<String[]> partitionFields;
+  private final Object[] partitionValues;
+
+  public HoodieBootstrapFileReader(HoodieFileReader<T> skeletonFileReader, HoodieFileReader<T> dataFileReader, Option<String[]> partitionFields, Object[] partitionValues) {
+    this.skeletonFileReader = skeletonFileReader;
+    this.dataFileReader = dataFileReader;
+    this.partitionFields = partitionFields;
+    this.partitionValues = partitionValues;
+  }
+
+  @Override
+  public String[] readMinMaxRecordKeys() {
+    return skeletonFileReader.readMinMaxRecordKeys();
+  }
+
+  @Override
+  public BloomFilter readBloomFilter() {
+    return skeletonFileReader.readBloomFilter();
+  }
+
+  @Override
+  public Set<String> filterRowKeys(Set<String> candidateRowKeys) {
+    return skeletonFileReader.filterRowKeys(candidateRowKeys);
+  }
+
+  @Override
+  public ClosableIterator<HoodieRecord<T>> getRecordIterator(Schema readerSchema, Schema requestedSchema) throws IOException {
+    ClosableIterator<HoodieRecord<T>> skeletonIterator = skeletonFileReader.getRecordIterator(readerSchema, requestedSchema);
+    ClosableIterator<HoodieRecord<T>> dataFileIterator = dataFileReader.getRecordIterator(HoodieAvroUtils.removeMetadataFields(readerSchema), requestedSchema);
+    return new ClosableIterator<HoodieRecord<T>>() {
+      @Override
+      public void close() {
+        skeletonIterator.close();
+        dataFileIterator.close();
+      }
+
+      @Override
+      public boolean hasNext() {
+        return skeletonIterator.hasNext() && dataFileIterator.hasNext();
+      }
+
+      @Override
+      public HoodieRecord<T> next() {
+        HoodieRecord<T> dataRecord = dataFileIterator.next();
+        HoodieRecord<T> skeletonRecord = skeletonIterator.next();
+        HoodieRecord<T> ret = dataRecord.prependMetaFields(readerSchema, readerSchema,
+            new MetadataValues().setCommitTime(skeletonRecord.getRecordKey(readerSchema, HoodieRecord.COMMIT_TIME_METADATA_FIELD))
+                .setCommitSeqno(skeletonRecord.getRecordKey(readerSchema, HoodieRecord.COMMIT_SEQNO_METADATA_FIELD))
+                .setRecordKey(skeletonRecord.getRecordKey(readerSchema, HoodieRecord.RECORD_KEY_METADATA_FIELD))
+                .setPartitionPath(skeletonRecord.getRecordKey(readerSchema, HoodieRecord.PARTITION_PATH_METADATA_FIELD))
+                .setFileName(skeletonRecord.getRecordKey(readerSchema, HoodieRecord.FILENAME_METADATA_FIELD)), null);
+        if (partitionFields.isPresent()) {
+          for (int i = 0; i < partitionValues.length; i++) {
+            int position = readerSchema.getField(partitionFields.get()[i]).pos();
+            setPartitionField(position, partitionValues[i], ret.getData());
+          }
+        }
+        return ret;
+      }
+    };
+  }
+
+  protected abstract void setPartitionField(int position, Object fieldValue, T row);
+
+  @Override
+  public Schema getSchema() {
+    return skeletonFileReader.getSchema();

Review Comment:
   How is this used?  I assume this only contains meta fields.



##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/clustering/run/strategy/MultipleSparkJobExecutionStrategy.java:
##########
@@ -327,21 +332,52 @@ private HoodieData<HoodieRecord<T>> readRecordsForGroupBaseFiles(JavaSparkContex
 
     // NOTE: It's crucial to make sure that we don't capture whole "this" object into the
     //       closure, as this might lead to issues attempting to serialize its nested fields
+    HoodieTableConfig  tableConfig = getHoodieTable().getMetaClient().getTableConfig();
+    String bootstrapBasePath = tableConfig.getBootstrapBasePath().orElse(null);
+    Option<String[]> partitionFields = tableConfig.getPartitionFields();
+    String timeZoneId = jsc.getConf().get("timeZone", SQLConf.get().sessionLocalTimeZone());
+    boolean shouldValidateColumns = jsc.getConf().getBoolean("spark.sql.sources.validatePartitionColumns", true);

Review Comment:
   Could this be moved to closure and use `hadoopConf.get()` to avoid additional variables passed?



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